22 citations · 32 across the 11 of their papers we have counts for
11 papers
Rethinking Two-Stage Referring-by-Tracking in Referring Multi-Object Tracking: Make it Strong Again
Weize Li, Yunhao Du, Qixiang Yin +2
Referring Multi-Object Tracking (RMOT) aims to track multiple objects specified by natural language expressions in videos. With the recent significant progress of one-stage methods…
Hierarchical IoU Tracking based on Interval
Yunhao Du, Zhicheng Zhao, Fei Su
Multi-Object Tracking (MOT) aims to detect and associate all targets of given classes across frames. Current dominant solutions, e.g. ByteTrack and StrongSORT++, follow the hybrid…
YYDS: Visible-Infrared Person Re-Identification with Coarse Descriptions
Yunhao Du, Zhicheng Zhao, Fei Su
Visible-infrared person re-identification (VI-ReID) is challenging due to considerable cross-modality discrepancies. Existing works mainly focus on learning modality-invariant feat…
iKUN: Speak to Trackers without Retraining
Yunhao Du, Cheng Lei, Zhicheng Zhao +1
Referring multi-object tracking (RMOT) aims to track multiple objects based on input textual descriptions. Previous works realize it by simply integrating an extra textual module i…
Video-based Visible-Infrared Person Re-Identification with Auxiliary Samples
Yunhao Du, Cheng Lei, Zhicheng Zhao +2
Visible-infrared person re-identification (VI-ReID) aims to match persons captured by visible and infrared cameras, allowing person retrieval and tracking in 24-hour surveillance s…
Dynamic Clustering and Cluster Contrastive Learning for Unsupervised Person Re-identification
Ziqi He, Mengjia Xue, Yunhao Du +2
Unsupervised Re-ID methods aim at learning robust and discriminative features from unlabeled data. However, existing methods often ignore the relationship between module parameters…
EnsembleMOT: A Step towards Ensemble Learning of Multiple Object Tracking
Yunhao Du, Zihang Liu, Fei Su
Multiple Object Tracking (MOT) has rapidly progressed in recent years. Existing works tend to design a single tracking algorithm to perform both detection and association. Though e…
OMG: Observe Multiple Granularities for Natural Language-Based Vehicle Retrieval
Yunhao Du, Binyu Zhang, Xiangning Ruan +3
Retrieving tracked-vehicles by natural language descriptions plays a critical role in smart city construction. It aims to find the best match for the given texts from a set of trac…
PAMI-AD: An Activity Detector Exploiting Part-attention and Motion Information in Surveillance Videos
Yunhao Du, Zhihang Tong, Junfeng Wan +2
Activity detection in surveillance videos is a challenging task caused by small objects, complex activity categories, its untrimmed nature, etc. Existing methods are generally limi…
GIAOTracker: A comprehensive framework for MCMOT with global information and optimizing strategies in VisDrone 2021
Yunhao Du, Junfeng Wan, Yanyun Zhao +3
In recent years, algorithms for multiple object tracking tasks have benefited from great progresses in deep models and video quality. However, in challenging scenarios like drone v…
StrongSORT: Make DeepSORT Great Again
Yunhao Du, Zhicheng Zhao, Yang Song +4
Recently, Multi-Object Tracking (MOT) has attracted rising attention, and accordingly, remarkable progresses have been achieved. However, the existing methods tend to use various b…